A historical perspective of template-based protein structure prediction

Area of Science:

• Bioinformatics and Computational Biology
• Structural Biology
• Molecular Modeling

Background:

• Protein structure prediction is a fundamental challenge in molecular biology.
• Understanding protein structure is crucial for deciphering biological function and disease mechanisms.
• Various computational approaches have been developed to predict protein structures from their amino acid sequences.

Observation:

• This chapter provides a historical overview of protein structure prediction methodologies.
• Key methods discussed include homology modeling, fold recognition (FR)/protein threading, and ab initio/de novo approaches.
• Hybrid techniques combining multiple prediction strategies are also introduced.

Findings:

• The historical progression of different protein structure prediction methods is detailed.
• Significant advancements in the field, especially in threading/FR, are reviewed.
• Progress is contextualized through major international assessments like the CASP/CAFASP contests.

Implications:

• The review offers insights into the evolution of computational structural biology.
• Understanding past progress informs current research and development in protein structure prediction.
• Identifying future challenges is essential for guiding the next generation of prediction tools and strategies.